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Mid LevelFull-timeRustAWSAzureMachine LearningTensorFlowPyTorchGitAI
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
PAR Technology Corporation is seeking an AI Engineer to help integrate AI capabilities into their restaurant technology solutions. This role involves designing and building intelligent pipelines that use LLMs, tools, and data to solve complex user and product problems.
Key Responsibilities
- →Design and build user-facing AI capabilities that simplify decision-making and enable faster action for operational teams
- →Create and maintain multi-step LLM workflows that combine prompts, tools, and data to execute complex tasks
- →Use retrieval-augmented generation (RAG) to combine internal data with LLMs and generate context-aware, trustworthy results
- →Deliver features that set PAR apart from the competition and provide tangible value to users
Requirements
- ✓5+ years’ experience as a software engineer, ideally within a SaaS or data-centric product environment
- ✓Proficiency with LLM platforms and APIs (e.g., OpenAI, Azure OpenAI)
- ✓Familiarity with prompt engineering, embedding models, and vector databases
- ✓Experience designing and implementing multi-step AI workflow chains (e.g., LangChain, Semantic Kernel, custom pipelines)
- ✓Strong data skills, including proficiency with SQL and structured datasets in production
- ✓Understanding of cloud-based orchestration tools like Azure Data Factory or equivalents
- ✓Experience taking AI features from prototype to production with attention to scalability, cost-efficiency, and observability
- ✓Strong communication skills and ability to work cross-functionally with product, engineering, and data teams
- ✓Recognized as an internal driver of AI strategy and implementation, setting standards and best practices for trustworthy, scalable AI
- ✓Additional Skills (Nice-to-Haves)
- ✓Experience working with data-rich applications, especially in retail, hospitality, or restaurant operations
- ✓Exposure to data visualization, analytics platforms, or reporting tools
- ✓Experience with traditional machine learning workflows (e.g., scikit-learn, TensorFlow, PyTorch)
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